Data engineering interns are in high demand. According to the Dice 2020 Tech Job Report, demand for data engineers grew 50% from 2018 to 2019. Interns can help fill this demand by handling entry-level tasks while gaining on-the-job training.
Just because data engineer internships are in demand doesn’t mean they’re easy to get. The NACE Center for Career Development and Talent Acquisition has found that people with paid internships are twice as likely to get a job offer after graduation than people who don’t intern—so it’s a competitive field. If you want to land a coveted data engineering internship, learn how in this step-by-step guide.
What Is a Data Engineering Internship?
Data engineers are responsible for building the infrastructure that turns raw data into information that data scientists can use. Data engineering interns help staff engineers by performing basic tasks while learning about database design.
According to Indeed, the average intern will help staff data engineers with tasks like data collection, integration, and monitoring. A typical internship lasts between a semester and a year. Many are aimed at students getting their BS or MS in data science, but there are still plenty of opportunities for people who are switching careers.
Pursuing an engineering internship is an excellent way to prepare yourself for a career in data engineering. Having experience in the field can help you decide whether you actually want to pursue it as a career.
If you decide to enter the field, data engineering is experiencing dramatic growth. Dice reports that in 2019, data engineers saw the fifth-highest salary growth rate in all of tech. Having an internship on your resume increases your chance of landing one of these jobs.
What Data Engineering Skills Do Employers Want?
Data engineering interns aren’t expected to know as much as full-time professional engineers. However, you’ll still need some basic skills in order to be considered. Excellent data engineering skills to put on your resume include:
- Database languages like SQL and NoSQL. Within a database, these languages control how information is stored and retrieved after a query. They’re crucial for doing any work with large datasets.
- Data APIs. Understanding how to implement data APIs allows you to connect databases with websites during web development.
- Machine learning. Understanding the basics of machine learning helps you understand how data scientists will use your infrastructure.
- ETL tools. ETL tools extract data from sources, transfer it into a more convenient form, and load it onto a new platform. Understanding how to use ETL will help you build better infrastructure for your employer.
What Is the Average Salary for a Data Engineering Intern?
Unlike some fields, internships in data engineering are typically paid. According to PayScale, the average engineering intern receives $17.62 per hour. The exact amount depends on the company, location, and combination of employer bids you receive.
How To Land a Data Engineering Internship in 5 Steps
Getting a data engineer internship doesn’t have to be complicated. By following these five steps, you can improve your chances of landing the role.
1. Find Potential Internships
The first step to getting an internship is finding positions that fit your needs. You can find data engineer intern jobs by searching websites for job postings, internship boards, and hiring pages for companies you’re interested in.
Today, many internships can be done remotely, so don’t ignore companies just because they’re far away. Organizations in places from San Francisco to Atlanta, Georgia, may offer you a flexible schedule at home. Instead, focus on internships that meet your experience, skills, and preferred company culture.
You may find internships that are designed to increase a company’s diversity and equity. These positions are built for candidates with a disability, veteran status, or protected race or sexual orientation. They’re intended to make it easier for less privileged job seekers to get into tech.
2. Get Hands-On Experience
Even for internships, employers prefer candidates with hands-on experience. You don’t need to work somewhere to get that experience, either. Taking on data engineering projects and classes on your own time is a great way to learn new skills and generate a portfolio that employers will appreciate.
3. Write a Great Resume
Once you have experience and know where you want to apply, you need a strong resume. Your resume is the first impression you make on a potential employer. Building a resume that’s interesting and follows tech industry standards will help you stand out from the competition. You can make your resume more engaging by focusing on your achievements instead of your duties and responsibilities.
For example, don’t just say you “managed a computer lab” at your student job. Instead, explain how you improved it by implementing new programs or adding new features. That’s immediately more interesting to the employer.
4. Apply the Right Way
No two businesses accept applications the same way. Read job ads carefully to make sure you submit your information correctly. For example, if a company asks you to email your resume to a specific person, write a cover letter, or submit two reference letters, make sure you do so. Submitting your resume without following instructions could affect your chances of getting the position.
5. Prepare for Interviews
If you’re short-listed for an interview, it’s time to do your research. Learn about the company and the role you want. Interviewers want you to care about the position enough to learn about it in advance.
You should also prepare answers to common interview questions. Feeling prepared can help you avoid getting nervous. It will also help you appear more professional.
Lastly, collect some questions to ask the interviewer. This is your chance to ask about hours, responsibilities, school credit, and anything else you want to know. It also helps you make a good impression since it shows you’re engaged in the hiring process.